Primary Gleason Pattern as a Predictor of Disease Progression in Gleason Score 7 Prostate Cancer
- 1 May 2001
- journal article
- Published by Wolters Kluwer Health in The American Journal of Surgical Pathology
- Vol. 25 (5) , 657-660
- https://doi.org/10.1097/00000478-200105000-00014
Abstract
Gleason score (GS) is a powerful predictor of disease progression in men with prostate cancer (PCa). The majority of clinically localized prostate cancers, however, are moderately (GS5/6) or moderate to poorly (GS7) differentiated tumors with indeterminate prognosis. Differences in disease progression between patients with GS5/6 and GS7 tumors suggest the presence of any component of high-grade tumor (Gleason pattern [GP] 4/5) worsens prognosis markedly. Indeed, McNeal et al. have shown that quantification of GP4/5 provides prognostic information beyond the standard GS. Few investigators have analyzed whether primary and secondary GPs are important prognostically within GS7 PCa. All 823 whole-mount radical prostatectomy specimens with GS7 from a single surgeon (P.T.S.) were analyzed. Tumors were either 3+4 or 4+3, and primary GP was assigned by the same pathologist (T.M.W.). A total of 643 patients with 3+4 tumors and 180 patients with 4+3 tumors were studied. Statistical analysis using the log-rank test showed a significant difference in recurrence-free survival between patients with primary GP4 and those with GP3 (p <0.0001). However, in multivariate analysis with preoperative prostate-specific antigen, total tumor volume, surgical margin status, and the presence or absence of seminal vesicle involvement, extraprostatic extension, and lymph node metastasis, the primary GP did not retain independent significance (p = 0.0557). GS7 PCa is a heterogeneous group of tumors. In this cohort of men with GS7 tumors treated by radical retropubic prostatectomy, primary GP showed a significant correlation with other histologic and clinical predictors of disease progression; however, it was not independently predictive of disease progression in multivariate analysis (p = 0.76).Keywords
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